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Computer Optics, 2016, Volume 40, Issue 6, Pages 895–903 (Mi co342)  

IMAGE PROCESSING, PATTERN RECOGNITION

Research of sparse representation method for ringing suppression

A. V. Umnova, A. S. Krylovb

a National Research University Higher School of Economics, Moscow, Russia
b Lomonosov Moscow State University, Moscow, Russia

Abstract: In this paper we suggest an algorithm for ringing suppression based on a sparse representation method. As one of its steps, the suggested method includes image deblurring based on the Wiener-Hunt deconvolution algorithm. The ringing suppression algorithm uses the signals' mutual coherence and sparsities analysis when dealing with the ringing effect based on the sparse representation method. We also analyze the mutual coherence and sparsities for blurred images and images with white Gaussian noise.

Keywords: ringing effect, sparse representations, mutual coherence.

Funding Agency Grant Number
Russian Science Foundation 14-11-00308
The work was partially funded by the Russian Science Foundation (RSF), grant No. 141100308.


DOI: https://doi.org/10.18287/2412-6179-2016-40-6-895-903

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Full text: http://www.computeroptics.smr.ru/.../400617.html
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Received: 29.06.2016
Accepted:30.10.2016

Citation: A. V. Umnov, A. S. Krylov, “Research of sparse representation method for ringing suppression”, Computer Optics, 40:6 (2016), 895–903

Citation in format AMSBIB
\Bibitem{UmnKry16}
\by A.~V.~Umnov, A.~S.~Krylov
\paper Research of sparse representation method for ringing suppression
\jour Computer Optics
\yr 2016
\vol 40
\issue 6
\pages 895--903
\mathnet{http://mi.mathnet.ru/co342}
\crossref{https://doi.org/10.18287/2412-6179-2016-40-6-895-903}


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